Reliable spatial uncertainty evaluation of object detection models is special interest and has been subject recent work. In this work, we review the existing definitions for calibration probabilistic regression tasks. We inspect properties common networks extend state-of-the-art recalibration methods. Our methods use a Gaussian process (GP) scheme that yields parametric distributions as output ...

During the past decades, large amounts of diffuse cadmium (Cd) and zinc (Zn) contaminated soil material have been deposited in the floodplains of the river Rhine in the Netherlands. As spatial information on soil quality is required at different scale levels covering the whole area, characterisation exclusively based on soil sampling and analysis is time-consuming and very expensive. A quicker ...

BACKGROUND Covariate measurement error is common in epidemiologic studies. Current methods for correcting measurement error with information from external calibration samples are insufficient to provide valid adjusted inferences. We consider the problem of estimating the regression of an outcome Y on covariates X and Z, where Y and Z are observed, X is unobserved, but a variable W that measures...